HOW CAN DATAJOURNALISM SAVEYOUR NEWSROOM?IJF 2012, PERUGIAMIRKO LORENZJOURNALIST, INFORMATION ARCHITECT, TRAINER
YES, MAYBE , NO?
MAYBE , NO?
MAYBE
PEOPLETOOLSBUSINESS MODEL
PEOPLE
ALWAYS ASK: COMPARED TO WHAT?
ALWAYS ASK: COMPARED TO WHAT?Edward Tufte: To be truthful and revealing, data graphics must bear on the question at the he...
SLOW WAKE UP PROCESS...What is keeping journalists from using data more and better? This interview with AronPilhofer revea...
SLOW WAKE UP PROCESS...What is keeping journalists from using data more and better? This interview with AronPilhofer revea...
Datenjournalismus Praxistraining                                                                                          ...
Datenjournalismus Praxistraining                                                                                          ...
TOOLS
TOOLS: DO MEDIA COMPANIES USE THEM?
TOOLS: DO MEDIA COMPANIES USE THEM?
WHAT KIND OF TOOLS?http://open.blogs.nytimes.com/2012/02/16/rnews-is-here-and-this-is-what-it-means/
COULD YOU TELL WHICH TOOL ISREALLY GOOD AND WHICH IS HELDTOGETHER BY DUCT TAPE?
BUSINESS MODEL
THINK THERE IS A WAY BACK TO PRINT?  Newspaper:                Web:  Something               Everything                 vs...
HOW DO DO IT BETTER: COLLECT DATA
Click on article to get to website.
THREE BIG CHALLENGESBEFORE WE CAN ANSWER THE QUESTIONPEOPLE: LEARN, EXPERIMENT, CREATE TEAMSTOOLS: STRUCTURE, RE-USE, RE-P...
Can data journalism save your newsroom?
Can data journalism save your newsroom?
Can data journalism save your newsroom?
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Can data journalism save your newsroom?

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My (short) presentation at the International Journalism Festival in Perugia, 2012. Great event, was fun to be on multiple panels with Aron Pilhofer, Simon Rogers, Dan Nguyen. This was part of the "School of Data Journalism" programme, organized by the European Journalism Centre (EJC).

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Transcript of "Can data journalism save your newsroom?"

  1. 1. HOW CAN DATAJOURNALISM SAVEYOUR NEWSROOM?IJF 2012, PERUGIAMIRKO LORENZJOURNALIST, INFORMATION ARCHITECT, TRAINER
  2. 2. YES, MAYBE , NO?
  3. 3. MAYBE , NO?
  4. 4. MAYBE
  5. 5. PEOPLETOOLSBUSINESS MODEL
  6. 6. PEOPLE
  7. 7. ALWAYS ASK: COMPARED TO WHAT?
  8. 8. ALWAYS ASK: COMPARED TO WHAT?Edward Tufte: To be truthful and revealing, data graphics must bear on the question at the heart of quantitative thinking:“Compared to what?, from: The Visual Display of Quantitative Information
  9. 9. SLOW WAKE UP PROCESS...What is keeping journalists from using data more and better? This interview with AronPilhofer reveals many of the problems. Original article: http://knightgarage.stanford.edu/2012/02/times-editor-says-media- German translation - with permission from Teresa Souza and Aron Pilhofer: http:// not-driven-to-data-journalism/ www.datenjournalist.de/aron-pilhofer-medien-sind-nicht-datengetrieben/
  10. 10. SLOW WAKE UP PROCESS...What is keeping journalists from using data more and better? This interview with AronPilhofer reveals many of the problems. Original article: http://knightgarage.stanford.edu/2012/02/times-editor-says-media- German translation - with permission from Teresa Souza and Aron Pilhofer: http:// not-driven-to-data-journalism/ www.datenjournalist.de/aron-pilhofer-medien-sind-nicht-datengetrieben/
  11. 11. Datenjournalismus Praxistraining Gelb = Teilnehmer arbeiten aktiv eigenem ProjektABZV (Bonn), 5.-9. September 2011Zeit Mo Di Mi Do Fr EINSTIEG & PLANUNG FINDEN & FILTERN VISUALISIERUNG VISUALISIERUNG PUBLIZIEREN Daten visualisieren09:00 Vorstellung und Datenquellen Zwischenstand: Einbindung in CMS/Blogs (Linda Rath-Wiggins/Cosmin Wochenübersicht (Wilfried Runde) Ideen der Teilnehmer Erfolgsmessung Cabulea Präsentation: Wochenprojekt:10:00 Datensätze suchen Grundformen Wochenprojekt Datenjournalismus Abschluss Data Scraping Wochenprojekt:11:00 Ideen und Erwartungen? (Linda Rath-Wiggins/Cosmin Spezielle Formen Wochenprojekt Abschluss Cabulea)12:00 Pause Pause Pause Pause Pause Vortrag: Präsentation: Zahlen visualisieren - Wochenprojekt:13:00 Data Scraping Wochenprojekt Von den Daten zur Story typische Fehler vermeiden Abschluss Analyse: Wie haben die das Analyse: Wie haben die das14:00 Daten visualisieren Ergebnisse präsentieren gemacht? gemacht? Workshop mit Gregor Aisch: Ausblick/ Wochenprojekt: Daten visualisieren15:00 Daten filtern Daten visualisieren Formate für Datenjournalismus Erstes Storyboard Abschlussdiskussion Wochenprojekt: Wochenprojekt:16:00 Erstes Storyboard Daten filtern Storyboard verfeinern17:00 Feedback/Tagesgespräch Feedback/Tagesgespräch Feedback/Tagesgespräch
  12. 12. Datenjournalismus Praxistraining Gelb = Teilnehmer arbeiten aktiv eigenem ProjektABZV (Bonn), 5.-9. September 2011Zeit Mo Di Mi Do Fr EINSTIEG & PLANUNG FINDEN & FILTERN VISUALISIERUNG VISUALISIERUNG PUBLIZIEREN Daten visualisieren09:00 Vorstellung und Datenquellen Zwischenstand: Einbindung in CMS/Blogs (Linda Rath-Wiggins/Cosmin Wochenübersicht (Wilfried Runde) Ideen der Teilnehmer Erfolgsmessung Cabulea Präsentation: Wochenprojekt:10:00 Datensätze suchen Grundformen Wochenprojekt Datenjournalismus Abschluss Data Scraping Wochenprojekt:11:00 Ideen und Erwartungen? (Linda Rath-Wiggins/Cosmin Spezielle Formen Wochenprojekt Abschluss Cabulea) In September 20112 we conducted a first, one-week traing for data-driven journalism12:00 Pause Bonn, Germany. Pause in Participants came fromPause Pause newspapers like Die Zeit, Süddeutsche.de, Pause Westfälische Nachrichten, Rheinische Post and others. Vortrag: Präsentation: Zahlen visualisieren - Wochenprojekt:13:00 Data Scraping Wochenprojekt Von den Daten zur Story typische Fehler vermeiden Abschluss Analyse: Wie haben die das Analyse: Wie haben die das14:00 Daten visualisieren Ergebnisse präsentieren gemacht? gemacht? Workshop mit Gregor Aisch: Ausblick/ Wochenprojekt: Daten visualisieren15:00 Daten filtern Daten visualisieren Formate für Datenjournalismus Erstes Storyboard Abschlussdiskussion Wochenprojekt: Wochenprojekt:16:00 Erstes Storyboard Daten filtern Storyboard verfeinern17:00 Feedback/Tagesgespräch Feedback/Tagesgespräch Feedback/Tagesgespräch
  13. 13. TOOLS
  14. 14. TOOLS: DO MEDIA COMPANIES USE THEM?
  15. 15. TOOLS: DO MEDIA COMPANIES USE THEM?
  16. 16. WHAT KIND OF TOOLS?http://open.blogs.nytimes.com/2012/02/16/rnews-is-here-and-this-is-what-it-means/
  17. 17. COULD YOU TELL WHICH TOOL ISREALLY GOOD AND WHICH IS HELDTOGETHER BY DUCT TAPE?
  18. 18. BUSINESS MODEL
  19. 19. THINK THERE IS A WAY BACK TO PRINT? Newspaper: Web: Something Everything vs. about about everything something
  20. 20. HOW DO DO IT BETTER: COLLECT DATA
  21. 21. Click on article to get to website.
  22. 22. THREE BIG CHALLENGESBEFORE WE CAN ANSWER THE QUESTIONPEOPLE: LEARN, EXPERIMENT, CREATE TEAMSTOOLS: STRUCTURE, RE-USE, RE-PURPOSEMODEL: FROM ATTENTION TO TRUST
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